TY - GEN
T1 - Cost-sensitive task routing and resource provisioning in geo-distributed clouds
AU - Yuan, Haitao
AU - Bi, Jing
AU - Zhou, Mengchu
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/1
Y1 - 2017/8/1
N2 - Many different types of applications simultaneously execute in current data centers (DCs). To provide low cost and improved performance, each application is typically deployed in distributed DCs. Tasks of users around the world first go through Internet service providers (ISPs) which deliver data between distributed DCs and users. However, capacities and bandwidth cost of different ISPs vary. Besides, energy cost of multiple DCs located in different geographical places is different. With the growth of tasks, the DC provider's energy and ISP bandwidth cost is huge and continues to increase. Therefore, due to the energy and bandwidth cost difference in different geographical places, it is highly difficult to minimize the DC provider's total cost. Therefore, to tackle the problem, this work proposes a cost-sensitive task routing approach that can jointly specify the optimal selection of available ISPs for the arriving tasks, and the optimal number of switched-on servers in each DC. Finally, the simulation with tasks in Google's data center shows the proposed cost-sensitive task routing approach can effectively decrease the DC provider's cost, and raise system throughput in comparison with some typical scheduling method.
AB - Many different types of applications simultaneously execute in current data centers (DCs). To provide low cost and improved performance, each application is typically deployed in distributed DCs. Tasks of users around the world first go through Internet service providers (ISPs) which deliver data between distributed DCs and users. However, capacities and bandwidth cost of different ISPs vary. Besides, energy cost of multiple DCs located in different geographical places is different. With the growth of tasks, the DC provider's energy and ISP bandwidth cost is huge and continues to increase. Therefore, due to the energy and bandwidth cost difference in different geographical places, it is highly difficult to minimize the DC provider's total cost. Therefore, to tackle the problem, this work proposes a cost-sensitive task routing approach that can jointly specify the optimal selection of available ISPs for the arriving tasks, and the optimal number of switched-on servers in each DC. Finally, the simulation with tasks in Google's data center shows the proposed cost-sensitive task routing approach can effectively decrease the DC provider's cost, and raise system throughput in comparison with some typical scheduling method.
KW - Cloud performance analysis
KW - Cost optimization
KW - Data center
KW - Task routing
UR - https://www.scopus.com/pages/publications/85028499526
U2 - 10.1109/ICNSC.2017.8000144
DO - 10.1109/ICNSC.2017.8000144
M3 - 会议稿件
AN - SCOPUS:85028499526
T3 - Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017
SP - 507
EP - 512
BT - Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017
A2 - Guerrieri, Antonio
A2 - Fortino, Giancarlo
A2 - Vasilakos, Athanasios V.
A2 - Zhou, MengChu
A2 - Lukszo, Zofia
A2 - Palau, Carlos
A2 - Liotta, Antonio
A2 - Vinci, Andrea
A2 - Basile, Francesco
A2 - Fanti, Maria Pia
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Networking, Sensing and Control, ICNSC 2017
Y2 - 16 May 2017 through 18 May 2017
ER -